Wearable Sensing’s wireless DSI-24 is the leading dry electrode EEG system in terms of signal quality and comfort. The DSI-24 takes on average less than 3 minutes to set up, making it the ideal solution for scientists in need of a simple, easy to use, EEG system. Our patented sensor technology not only delivers uncompromised signal quality but also enables our system to be virtually immune against motion and electrical artifacts. As a result, the DSI-24 can be utilized in virtual or augmented reality, while also allowing researchers to take their experiments out of the lab, and into the real world.
The DSI-24 has sensors that provide full head coverage with 19 electrodes on the head, 2 earclip sensors, and also has 3 built-in auxiliary inputs for acquisition of up to 3 auxiliary sensors. It also has an 8-bit trigger input to synchronize with other devices such as Eye-Tracking, Motion (IMU), and more.
Used around the world by leaders in Research, Neurofeedback, Neuromarketing, Brain-Computer Interfaces, & Neuroergonomics.
With over 90% correlation to research-grade wet EEG systems, the dry sensor interface (DSI) offers unparalleled quality and performance
Multiple adjustment points and a foam pad lined interior enable the system to be worn for up to 8 hours on any head shape or size
All DSI systems include free, unlimited licenses of DSI-Streamer, our data acquisition software which can record raw data, in .csv and .edf file formats
Faraday cage's, spring-loaded electrodes, and our patented common-mode follower technology, provides near immunity against electrical and motion artifacts
Using 70% isopropyl alcohol and a cleaning brush, the DSI-24 only takes a minute to clean, 3 minutes to dry, and can be up and running on the next subject in minutes
All DSI systems include our free C based .dll API, which enables users to pull the raw data directly from the headset, for custom software on Windows, Mac OS, Linux, and ARM
The DSI-24 was designed for ultra-rapid setup, taking on average less than 3 minutes to don, and works on any type of hair, including long hair, thick hair, afros, and more
DSI headsets have active sensors, amplifiers, digitizers, batteries, onboard storage, and wireless transmission, making them complete, mobile, wearable EEG systems
DSI systems exclusively work with QStates, a machine learning algorithm for cognitive classification on states such as mental workload, engagement, and fatigue
Our Wireless Trigger Hub simplifies the synchronization of DSI headsets with other devices. It features:
An additional benefit of the Trigger Hub design is that it allows synchronization across multiple data sources that are distributed across multiple systems, each of which running at its own clock rate. One such case commonly experienced in EEG experiments involves the synchronization of EEG and eye-tracking measurements, where the inevitable clock drift that arises between two systems during extended measurements creates difficulty in aligning data to events across the two systems.
The DSI-24 has 3 auxiliary inputs on the headset, which allows for automatic synchronization of Wearable Sensing’s auxiliary sensors to the EEG. The sensors available include ECG, EMG, EOG, GSR, RESP, & TEMP. The sensor data is collected and recorded in our data acquisition software, DSI-Streamer, where you can view the EEG and Aux sensors in real-time.
EEG Channels
Fp1, Fp2, Fz, F3, F4, F7, F8, Cz, C3, C4, T7/T3, T8/T4, Pz, P3, P4, P7/T5, P8/T6, O1, O2, A1, A2
Reference / Ground
Common Mode Follower / Fpz
Head Size Range
Adult Size: 52cm – 62cm circumference
Child Size: 48cm – 54cm circumference
Sampling Rate
300 Hz (600Hz upgrade available)
Bandwidth
0.003 – 150 Hz
A/D resolution
0.317 μV referred to input
Input Impedance (1Hz)
47 GΩ
CMRR
> 120 dB
Amplifier / Digitizer
16 bits / 24 channels
Wireless
Bluetooth
Wireless Range
10 m
Run-time
> 24 Hours, Hot-Swappable Batteries
Onboard Storage
~ 68 Hours (available option)
Data Acquisition
Real time, evoked potentials
Signal Quality Monitoring
Continuous impedance, Baseline offset, Noise (1-50 Hz)
Data Type
Raw and Filtered Data available
File Type
.CSV and .EDF
Data Output Streaming
TCP/IP socket, API (C Based), LSL
Cognitive State Classification
Brain Computer Interface
SSVEP BCI Algorithms; BCI2000; OpenViBE; PsychoPy; BCILab
Data Integration / Analysis
CAPTIV; Lab Streaming Layer; NeuroPype; BrainStorm; NeuroVIS
Neurofeedback
Applied Neuroscience NeuroGuide; Brainmaster Brain Avatar; EEGer
Neuromarketing
CAPTIV Neurolab
Presentation
Presentation; E-Prime
Arakaki, Xianghong; Lee, Ryan; King, Kevin S; Fonteh, Alfred N; Harrington, Michael G
Alpha desynchronization during simple working memory unmasks pathological aging in cognitively healthy individuals Journal Article
In: PloS one, vol. 14, no. 1, pp. e0208517, 2019.
@article{arakaki2019alpha,
title = {Alpha desynchronization during simple working memory unmasks pathological aging in cognitively healthy individuals},
author = {Xianghong Arakaki and Ryan Lee and Kevin S King and Alfred N Fonteh and Michael G Harrington},
editor = {Stephen D. Ginsberg, Nathan S Kline Institute},
doi = {https://doi.org/10.1371/journal.pone.0208517},
year = {2019},
date = {2019-01-02},
journal = {PloS one},
volume = {14},
number = {1},
pages = {e0208517},
publisher = {Public Library of Science San Francisco, CA USA},
abstract = {Our aim is to explore if cognitive challenge combined with objective physiology can reveal abnormal frontal alpha event-related desynchronization (ERD), in early Alzheimer’s disease (AD). We used quantitative electroencephalography (qEEG) to investigate brain activities during N-back working memory (WM) processing at two different load conditions (N = 0 or 2) in an aging cohort. We studied 60–100 year old participants, with normal cognition, and who fits one of two subgroups from cerebrospinal fluid (CSF) proteins: cognitively healthy (CH) with normal amyloid/tau ratio (CH-NAT, n = 10) or pathological amyloid/tau ratio (CH-PAT, n = 14). We recorded behavioral performances, and analyzed alpha power and alpha spectral entropy (SE) at three occasions: during the resting state, and at event-related desynchronization (ERD) [250 ~ 750 ms] during 0-back and 2-back. During 0-back WM testing, the behavioral performance was similar between the two groups, however, qEEG notably differentiated CH-PATs from CH-NATs on the simple, 0-back testing: Alpha ERD decreased from baseline only in the parietal region in CH-NATs, while it decreased in all brain regions in CH-PATs. Alpha SE did not change in CH-NATs, but was increased from baseline in the CH-PATs in frontal and left lateral regions (p<0.01), and was higher in the frontal region (p<0.01) of CH-PATs compared to CH-NATs. The alpha ERD and SE analyses suggest there is frontal lobe dysfunction during WM processing in the CH-PAT stage. Additional power and correlations with behavioral performance were also explored. This study provide pilot information to further evaluate whether this biomarker has clinical significance.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Camp, Marieke Van; Boeck, Muriel De; Verwulgen, Stijn; Bruyne, Guido De
EEG Technology for UX Evaluation: A Multisensory Perspective Conference
International Conference on Applied Human Factors and Ergonomics, vol. 775, Springer Advances in Intelligent Systems and Computing , 2018.
@conference{van2018eeg,
title = {EEG Technology for UX Evaluation: A Multisensory Perspective},
author = {Marieke Van Camp and Muriel De Boeck and Stijn Verwulgen and Guido De Bruyne},
url = {https://link.springer.com/chapter/10.1007/978-3-319-94866-9_34},
year = {2018},
date = {2018-06-28},
booktitle = {International Conference on Applied Human Factors and Ergonomics},
volume = {775},
pages = {337--343},
publisher = {Advances in Intelligent Systems and Computing },
organization = {Springer},
abstract = {Along with a growing interest in experience-driven design, interest in measuring user experience has progressively increased. This study explores the use of EEG for empirical UX evaluation. A first experimental test was conducted to measure and understand the effect of sensory stimuli on the user experience. A first experimental test was carried out with eight participants. A series of videos, eliciting positive and negative emotional responses, were presented to the participants. Subsequently, auditory stimuli were introduced and the effect on the user experience was evaluated using EEG measurements techniques and analysis software. After the tests the participants were questioned to verify whether the subjective results matched the objective measurements.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Memmott, Tab; Eddy, Brandon; Dabiri, Sina; Erdogmus, Deniz; Fried-Oken, Melanie; Oken, Barry
Automated and self-report measures of drowsiness over successive calibrations in a brain-computer interface for communication Journal Article
In: Clinical Neurophysiology, vol. 129, pp. e61–e62, 2018.
@article{memmott2018t154,
title = {Automated and self-report measures of drowsiness over successive calibrations in a brain-computer interface for communication},
author = {Tab Memmott and Brandon Eddy and Sina Dabiri and Deniz Erdogmus and Melanie Fried-Oken and Barry Oken},
doi = {https://doi.org/10.1016/j.clinph.2018.04.155},
year = {2018},
date = {2018-05-01},
journal = {Clinical Neurophysiology},
volume = {129},
pages = {e61--e62},
publisher = {Elsevier},
abstract = {Brain computer interfaces (BCI) generally require the user to maintain an attentive state. Potential end-users with severe speech and physical impairments may have limited communication abilities to report their current state, thus an automatic calculation of state may improve performance. It’s not yet known if an effective automatic calculation of drowsiness can be detected reliably in end-user populations or healthy controls.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Arakaki, Xianghong; Shoga, Michael; Li, Lianyang; Zouridakis, George; Tran, Thao; Fonteh, Alfred N; Dawlaty, Jessica; Goldweber, Robert; Pogoda, Janice M; Harrington, Michael G
Alpha desynchronization/synchronization during working memory testing is compromised in acute mild traumatic brain injury (mTBI) Journal Article
In: PloS one, vol. 13, no. 2, pp. e0188101, 2018.
@article{arakaki2018alpha,
title = {Alpha desynchronization/synchronization during working memory testing is compromised in acute mild traumatic brain injury (mTBI)},
author = {Xianghong Arakaki and Michael Shoga and Lianyang Li and George Zouridakis and Thao Tran and Alfred N Fonteh and Jessica Dawlaty and Robert Goldweber and Janice M Pogoda and Michael G Harrington},
doi = {https://doi.org/10.1371/journal.pone.0188101},
year = {2018},
date = {2018-02-14},
journal = {PloS one},
volume = {13},
number = {2},
pages = {e0188101},
publisher = {Public Library of Science San Francisco, CA USA},
abstract = {Diagnosing and monitoring recovery of patients with mild traumatic brain injury (mTBI) is challenging because of the lack of objective, quantitative measures. Diagnosis is based on description of injuries often not witnessed, subtle neurocognitive symptoms, and neuropsychological testing. Since working memory (WM) is at the center of cognitive functions impaired in mTBI, this study was designed to define objective quantitative electroencephalographic (qEEG) measures of WM processing that may correlate with cognitive changes associated with acute mTBI. First-time mTBI patients and mild peripheral (limb) trauma controls without head injury were recruited from the emergency department. WM was assessed by a continuous performance task (N-back). EEG recordings were obtained during N-back testing on three occasions: within five days, two weeks, and one month after injury. Compared with controls, mTBI patients showed abnormal induced and evoked alpha activity including event-related desynchronization (ERD) and synchronization (ERS). For induced alpha power, TBI patients had excessive frontal ERD on their first and third visit. For evoked alpha, mTBI patients had lower parietal ERD/ERS at the second and third visits. These exploratory qEEG findings offer new and non-invasive candidate measures to characterize the evolution of injury over the first month, with potential to provide much-needed objective measures of brain dysfunction to diagnose and monitor the consequences of mTBI.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hunter, Aimee M; Nghiem, Thien X; Cook, Ian A; Krantz, David E; Minzenberg, Michael J; Leuchter, Andrew F
In: Clinical EEG and Neuroscience, vol. 49, no. 5, pp. 306–315, 2017.
@article{hunter2018change,
title = {Change in quantitative EEG theta cordance as a potential predictor of repetitive transcranial magnetic stimulation clinical outcome in major depressive disorder},
author = {Aimee M Hunter and Thien X Nghiem and Ian A Cook and David E Krantz and Michael J Minzenberg and Andrew F Leuchter},
doi = {https://doi.org/10.1177/1550059417746212},
year = {2017},
date = {2017-12-10},
urldate = {2017-12-10},
journal = {Clinical EEG and Neuroscience},
volume = {49},
number = {5},
pages = {306--315},
publisher = {Sage Publications Sage CA: Los Angeles, CA},
abstract = {Repetitive transcranial magnetic stimulation (rTMS) has demonstrated efficacy in major depressive disorder (MDD), although clinical outcome is variable. Change in the resting-state quantitative electroencephalogram (qEEG), particularly in theta cordance early in the course of treatment, has been linked to antidepressant medication outcomes but has not been examined extensively in clinical rTMS. This study examined change in theta cordance over the first week of clinical rTMS and sought to identify a biomarker that would predict outcome at the end of 6 weeks of treatment. Clinically stable outpatients (n = 18) received nonblinded rTMS treatment administered to the dorsolateral prefrontal cortex (DLPFC). Treatment parameters (site, intensity, number of pulses) were adjusted on an ongoing basis guided by changes in symptom severity rating scale scores. qEEGs were recorded at pretreatment baseline and after 1 week of left DLPFC (L-DLPFC) rTMS using a 21-channel dry-electrode headset. Analyses examined the association between week 1 regional changes in theta band (4-8 Hz) cordance, and week 6 patient- and physician-rated outcomes. Theta cordance change in the central brain region predicted percent change in Inventory of Depressive Symptomology–Self-Report (IDS-SR) score, and improvement versus nonimprovement on the Clinical Global Impression–Improvement Inventory (CGI-I) (R2 = .38, P = .007; and Nagelkerke R2 = .78, P = .0001, respectively). The cordance biomarker remained significant when controlling for age, gender, and baseline severity. Treatment-emergent change in EEG theta cordance in the first week of rTMS may predict acute (6-week) treatment outcome in MDD. This oscillatory synchrony biomarker merits further study in independent samples.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mills, Caitlin; Fridman, Igor; Soussou, Walid; Waghray, Disha; Olney, Andrew M; D'Mello, Sidney K
Put your thinking cap on: detecting cognitive load using EEG during learning Conference
Proceedings of the Seventh International Learning Analytics & Knowledge Conference, 2017.
@conference{mills2017put,
title = {Put your thinking cap on: detecting cognitive load using EEG during learning},
author = {Caitlin Mills and Igor Fridman and Walid Soussou and Disha Waghray and Andrew M Olney and Sidney K D'Mello},
doi = {https://doi.org/10.1145/3027385.3027431},
year = {2017},
date = {2017-03-01},
booktitle = {Proceedings of the Seventh International Learning Analytics & Knowledge Conference},
pages = {80--89},
abstract = {Current learning technologies have no direct way to assess students' mental effort: are they in deep thought, struggling to overcome an impasse, or are they zoned out? To address this challenge, we propose the use of EEG-based cognitive load detectors during learning. Despite its potential, EEG has not yet been utilized as a way to optimize instructional strategies. We take an initial step towards this goal by assessing how experimentally manipulated (easy and difficult) sections of an intelligent tutoring system (ITS) influenced EEG-based estimates of students' cognitive load. We found a main effect of task difficulty on EEG-based cognitive load estimates, which were also correlated with learning performance. Our results show that EEG can be a viable source of data to model learners' mental states across a 90-minute session.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Halford, Jonathan J; Schalkoff, Robert J; Satterfield, Kevin E; Martz, Gabriel U; Kutluay, Ekrem; Waters, Chad G; Dean, Brian C
Comparison of a Novel Dry Electrode Headset to Standard Routine EEG in Veterans Journal Article
In: Journal of Clinical Neurophysiology, vol. 33, no. 6, pp. 530–537, 2016.
@article{halford2016comparison,
title = {Comparison of a Novel Dry Electrode Headset to Standard Routine EEG in Veterans},
author = {Jonathan J Halford and Robert J Schalkoff and Kevin E Satterfield and Gabriel U Martz and Ekrem Kutluay and Chad G Waters and Brian C Dean},
doi = {10.1097/WNP.0000000000000284},
year = {2016},
date = {2016-12-01},
journal = {Journal of Clinical Neurophysiology},
volume = {33},
number = {6},
pages = {530--537},
publisher = {LWW},
abstract = {Objective:
This purpose of this study was to evaluate the usefulness of a prototype battery-powered dry electrode system (DES) EEG recording headset in Veteran patients by comparing it with standard EEG.
Methods:
Twenty-one Veterans had both a standard electrode system recording and DES recording in nine different patient states at the same encounter. Setup time, patient comfort, and subject preference were measured. Three experts performed technical quality rating of each EEG recording in a blinded fashion using the web-based EEGnet system. Power spectra were compared between DES and standard electrode system recordings.
Results:
The average time for DES setup was 5.7 minutes versus 21.1 minutes for standard electrode system. Subjects reported that the DES was more comfortable during setup. Most subjects (15 of 21) preferred the DES. On a five-point scale (1—best quality to 5—worst quality), the technical quality of the standard electrode system recordings was significantly better than for the DES recordings, at 1.25 versus 2.41 (P < 0.0001). But experts found that 87% of the DES EEG segments were of sufficient technical quality to be interpretable.
Conclusions:
This DES offers quick and easy setup and is well tolerated by subjects. Although the technical quality of DES recordings was less than standard EEG, most of the DES recordings were rated as interpretable by experts.
Significance:
This DES, if improved, could be useful for a telemedicine approach to outpatient routine EEG recording within the Veterans Administration or other health system.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Arakaki, Xianghong; Shoga, Michael; Li, Lianyang; Zouridakis, George; Rostami, Ramona; Goldweber, Robert; Harrington, Michael
Exploring neuroplasticity in acute mild traumatic brain injury Journal Article
In: The FASEB Journal, vol. 30, pp. 992–4, 2016.
@article{arakaki2016exploring,
title = {Exploring neuroplasticity in acute mild traumatic brain injury},
author = {Xianghong Arakaki and Michael Shoga and Lianyang Li and George Zouridakis and Ramona Rostami and Robert Goldweber and Michael Harrington},
url = {https://faseb.onlinelibrary.wiley.com/doi/abs/10.1096/fasebj.30.1_supplement.992.4},
year = {2016},
date = {2016-04-01},
journal = {The FASEB Journal},
volume = {30},
pages = {992--4},
publisher = {The Federation of American Societies for Experimental Biology},
abstract = {Objectives
To explore neuroplasticity in a longitudinal study of acute mild traumatic brain injury (mTBI).
Methods
We are using quantitative electroencephalography (qEEG) and magnetoencephalography (MEG) during the resting state and during cognitive brain stress to explore neuroplasticity in an ongoing acute mild traumatic brain injury research. Acute mTBI patients are recruited from the emergency department of Huntington Memorial Hospital in Pasadena, CA, and controls are non‐head‐trauma patients. Brain stress includes the N‐back (0‐back and 2‐back) working memory test and Color‐Word Interference Test (CWIT), administered using E‐prime software. Data were collected at three time points: within 1 week of injury, 14 days, and 30 days after injury. Behavioral as well as MEG and qEEG analysis are performed to compare the two groups.
Results
Resting MEG detected low frequency activity in the mTBI group, consistent with previous publications. N‐back, in particular during 2‐back trials, and CWIT, in particular during incongruent trials, both show initial executive function impairment that improved on later visits. Time frequency analysis suggested corresponding compromised brain activity.
Conclusions
The EEG/MEG recordings during rest and brain stress are objective and sensitive to neuroplasticity in acute mTBI, and could be potential objective mTBI markers.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Kang, Dayoon; Kim, Jinsoo; Jang, Dong-Pyo; Cho, Yang Seok; Kim, Sung-Phil
Investigation of engagement of viewers in movie trailers using electroencephalography Journal Article
In: Brain-Computer Interfaces, vol. 2, no. 4, pp. 193–201, 2015.
@article{kang2015investigation,
title = {Investigation of engagement of viewers in movie trailers using electroencephalography},
author = {Dayoon Kang and Jinsoo Kim and Dong-Pyo Jang and Yang Seok Cho and Sung-Phil Kim},
doi = {https://doi.org/10.1080/2326263X.2015.1103591},
year = {2015},
date = {2015-11-10},
journal = {Brain-Computer Interfaces},
volume = {2},
number = {4},
pages = {193--201},
publisher = {Taylor & Francis},
abstract = {Brain-computer interfaces (BCIs) have been focused on providing direct communications to the disabled. Recently, BCI researchers have expanded BCI applications to non-medical uses and categorized them as active BCI, reactive BCI, and passive BCI. Neurocinematics, a new application of reactive BCIs, aims to understand viewers’ cognitive and affective responses to movies from neural activity, providing more objective information than traditional subjective self-reports. However, studies on analytical indices for neurocinematics have verified their indices by comparisons with self-reports. To overcome this contradictory issue, we proposed using an independent psychophysical index to evaluate a neural engagement index (NEI). We made use of the secondary task reaction time (STRT), which measures participants’ engagement in a primary task by their reaction time to a secondary task; here, responding to a tactile stimulus was the secondary task and watching a movie trailer was the primary task. NEI was developed as changes in the difference between frontal beta and alpha activity of EEG. We evaluated movie trailers using NEI, STRT, and self-reports and found a significant correlation between STRT and NEI across trailers but no correlation between any of the self-report results and STRT or NEI. Our results suggest that NEI developed for neurocinematics may conform well with more objective psychophysical assessments but not with subjective self-reports.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Li, Lianyang; Pagnotta, Mattia F; Arakaki, Xianghong; Tran, Thao; Strickland, David; Harrington, Michael; Zouridakis, George
Brain activation profiles in mTBI: Evidence from combined resting-state EEG and MEG activity Conference
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE IEEE, Milan, Italy, 2015, ISSN: 1558-4615.
@conference{li2015brain,
title = {Brain activation profiles in mTBI: Evidence from combined resting-state EEG and MEG activity},
author = {Lianyang Li and Mattia F Pagnotta and Xianghong Arakaki and Thao Tran and David Strickland and Michael Harrington and George Zouridakis},
doi = {10.1109/EMBC.2015.7319994},
issn = {1558-4615},
year = {2015},
date = {2015-11-05},
booktitle = {2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
pages = {6963--6966},
publisher = {IEEE},
address = {Milan, Italy},
organization = {IEEE},
abstract = {In this study, we compared the brain activation profiles obtained from resting state Electroencephalographic (EEG) and Magnetoencephalographic (MEG) activity in six mild traumatic brain injury (mTBI) patients and five orthopedic controls, using power spectral density (PSD) analysis. We first estimated intracranial dipolar EEG/MEG sources on a dense grid on the cortical surface and then projected these sources on a standardized atlas with 68 regions of interest (ROIs). Averaging the PSD values of all sources in each ROI across all control subjects resulted in a normative database that was used to convert the PSD values of mTBI patients into z-scores in eight distinct frequency bands. We found that mTBI patients exhibited statistically significant overactivation in the delta, theta, and low alpha bands. Additionally, the MEG modality seemed to better characterize the group of individual subjects. These findings suggest that resting-state EEG/MEG activation maps may be used as specific biomarkers that can help with the diagnosis of and assess the efficacy of intervention in mTBI patients.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
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